bridging the gap: analyzing data in and below the cloud
TRANSCRIPT
The Briefing Room
Bridging the Gap: Analyzing Data In and Below the Cloud
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The Briefing Room
! Reveal the essential characteristics of enterprise software, good and bad
! Provide a forum for detailed analysis of today’s innovative technologies
! Give vendors a chance to explain their product to savvy analysts
! Allow audience members to pose serious questions... and get answers!
Mission
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Topics
This Month: CLOUD
August: ANALYTIC PLATFORMS
September: ANALYTICS
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Cloud
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Analyst: Dean Abbott
Dean Abbott is President of Abbott Analytics, Inc. Dean has more than 21 years of experience applying advanced data mining, data preparation and data visualization methods in real-world data-intensive problems, including fraud detection, response modeling, survey analysis, planned giving, predictive toxicology, signal process and missile guidance. He has developed and evaluated algorithms for use in commercial data mining and pattern recognition products, including polynomial networks, neural networks, radial basis functions and clustering algorithms. He is a seasoned instructor, having taught a wide range of data mining tutorials and seminars.
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! Tableau builds software for data visualization, business intelligence and analytics
! Its latest release, Tableau 8.0, offers new capabilities such as native connectors to cloud-based applications (Salesforce.com, Google Analytics and BigQuery, Amazon Redshift) and Tableau Online, a hosted version of Tableau Server
! These added features enable access to BI and analytics in the cloud using both on-premise and cloud-based data
Tableau Software
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Ellie Fields
Ellie Fields is the Director of Product Marketing at Tableau Software. She has spoken at numerous industry events for business intelligence as well as for data journalism. Prior to Tableau, Ellie worked at Microsoft and in late-stage venture capital. Ellie is a graduate of Rice University and the Stanford Graduate School of Business.
Tableau Desktop For Anyone
• Explore and visualize data • Self-service analytics for everyone • Blazing speed against massive data
Tableau Server For Organizations
• Complete business intelligence system • Web dashboards and applications • Secure information management • Enterprise scalability
Fast, easy, beautiful self-service analytics
for everyone
Tableau Server
running
in the Cloud
Start fast
Stay secure
Work anywhere
Grow smart
Fast, Flexible Deployment
76% Choose Cloud for Speed to Deploy
IDC
Sandeep Varma, Herring Creek Capital
Easy Mobile Access
No VPN or DMZ Required
Easy to Secure
Easy sharing
Greg Sheldon, Chief InformaKon Officer at Elite Brands.
Greg Sheldon, Chief InformaKon Officer at Elite Brands.
Tableau Online
Tableau Online
On-‐Premise Data (push)
Tableau Online
Cloud Data (pull) On-‐Premise Data
(push)
Usable
BY EVERYONE Accessible
EVERYWHERE
Easily
EVERYPLACE Applicable
TO ALL DATA
Simple Pricing
$500 per user per year
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Perceptions & Questions
Analyst: Dean Abbott
Analyzing Data in the Cloud
Dean Abbott Abbott Analytics, Inc.
July 23, 2013
Email: [email protected] Blog: http://abbottanalytics.blogspot.com
Twitter: @deanabb
© Abbott Analytics, Inc. 2001-2013 31
What is a Cloud?
• Hardware that isn’t “here”
• Flexible hardware and virtual machines • Don’t worry about size—grow as needed • Don’t worry about time—only pay for what you use
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How Big is Big?
• Most analytics projects use small data • 10Ks to 1Ms of records; < 1GB; desktop tools
• Some analytics projects use medium data • > k GB; too big for comfortable laptop/standard desktop • Fits into server -> client – server architecture
• A few analytics projects use true big data • 10s GB active processing • Leverage specialty software / hardware
• Column stores; high performance database
• Cloud (Google File System, Hadoop)
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Predictive Analytics in the Cloud
• Analytics (BI, BA, PA, DM): Data-Driven Decisions
• Predictive Analytics: Data-Driven Decisions using machine learning / statistics / AI • Automated discovery of which variables relate to target
variable • Building potentially complex, multi-dimensional, nonlinear
relationships between inputs and target
• Visualization of PA: Data Insight • Show how variables relate to target • Informs decision-makers why key variables are important in
predictions
Obstacles
• Setup costs • Not IT setup costs, but there are still infrastructure costs
• Integration with operational systems
• The cloud environment is a silo.
• Connectivity
• Real-time operational systems vs. the analyst sandbox
• Security
• Or perception of security issues
• Public/secure cloud vs. private servers © Abbott Analytics, Inc. 2001-2013 35
Questions
1. How flexible is the query environment for visualization? How easy is it to change the variables and slices one needs to visualize? (cloud vs. local OLAP cubes)
2. How would an analyst interact with the cloud environment to do Exploratory Data Analysis (EDA)?
1. What is the framework to connect with data mining / predictive analytics software?
3. What strategies do you recommend for reducing data flow to / from the cloud environment?
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The Briefing Room
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The Briefing Room
July: CLOUD
August: ANALYTIC PLATFORMS
September: ANALYTICS
Upcoming Topics
www.insideanalysis.com
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Thank You for Your
Attention
Image credit for Slide 5: yukipon / 123RF Stock Photo